Data Processing Methods for a High Throughput Brain Imaging PET Research Center

We describe a computer system designed to meet the data processing needs of a high-volume brain PET research center based on the High Resolution Research Tomograph (HRRT). Listmode data are collected by an acquisition computer and stored on a high-speed disk. A workflow management program transfers the data through a gigabit network, rebins events into sinograms, and calculates correction factors. Reconstruction jobs are performed on a 64 processor cluster. We developed methods for dynamically allocating subclusters from the pool of available nodes, and reconstructing multiple images on multiple subclusters simultaneously. We also studied overall workflow. In our initial plan, scatter and randoms calculation unexpectedly became a bottleneck. We therefore adjusted our plan so that scatter estimation was performed initially in low resolution, and later expanded to high resolution.

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